Recent developments in magneto-hydrodynamic

Journal of Molecular Liquids 250 (2018) 244–258

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Journal of Molecular Liquids journal homepage: www.elsevier.com/locate/molliq

Review

Recent developments in magneto-hydrodynamic Fe3O4 nanofluids for different molecular applications: A review study M. Hatami a,b,⁎, S. Mohammadi-Rezaei a, M. Tahari a, D. Jing b,⁎⁎ a b

Esfarayen University of Technology (EUT), Esfarayen, North Khorasan, Iran International Research Center for Renewable Energy, State Key Laboratory of Multiphase Flow in Power Engineering, Xi'an Jiaotong University, Xi'an 710049, China

a r t i c l e

i n f o

a b s t r a c t

Article history: Received 2 October 2017 Received in revised form 19 November 2017 Accepted 28 November 2017 Available online xxxx

In this review study, it is tried to collect all the recent studies in the magneto-hydrodynamic (MHD) nanofluids flow application using Fe3O4 nanoparticles. The studies are categorized by focusing more on seven different sections: Magnetic field effect, Friction and thermal (Heat transfer) effects, Viscosity and Physical properties, Thermal applications, Thermo-physcial studies, Works on synthesis and other applications. Also, the energy application of this type of nanofluid such as in microchannels, CO2 storages, U-tubes, L shaped geometries in solar application channels, etc. are reviewed and their results were discussed. Although the studies had valuable separate outcomes, but approximately all of them confirmed that by increasing the Reynolds number and volume fraction, Nusselt number increased and friction factor decreased. Furthermore, the friction-factor is increased with increase of volume concentration in most applications. © 2017 Elsevier B.V. All rights reserved.

Keywords: Fe3O4 Nanofluid Thermal application Synthesis Friction factor

Contents 1. 2.

Introduction . . . . . . . . . . . Recent studies . . . . . . . . . . 2.1. Magnetic field effect . . . . 2.2. Friction and thermal studies . 2.3. Viscosity and thermal effects. 2.4. Thermal applications . . . . 2.5. Thermo-physic studies . . . 2.6. Synthesis works . . . . . . 2.7. Other applications . . . . . 3. Conclusion . . . . . . . . . . . . Acknowledgment . . . . . . . . . . . References. . . . . . . . . . . . . . .

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1. Introduction One of the main objectives of engineering and industry, especially in dealing with the issue of heat transfer in the heat exchangers are nanofluids as a new generation of fluids with many applications. Nano-fluid, the term was introduced for the first time by the Choi [1],

⁎ Corresponding author at: Esfarayen University of Technology (EUT), Esfarayen, North Khorasan, Iran. ⁎⁎ Corresponding author. E-mail addresses: [email protected] (M. Hatami), [email protected] (D. Jing).

https://doi.org/10.1016/j.molliq.2017.11.171 0167-7322/© 2017 Elsevier B.V. All rights reserved.

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a colloidal solution formed from a base fluid and solid nanoparticles. Nanofluids previously were used to increase the thermal conductivity of fluids by micrometer-sized particles added to base fluid. The particles in suspension did not have the necessary stability and quickly settle while nano-sized particles form a stable suspension. Distribution of nanoparticles in a typical fluids can improve heat transfer properties or in other words to increase the thermal conductivity of fluid. Harandi et al. [2] prepared a nanofluid consists of Fe 3 O 4 nanoparticles for the first time and functionalized multi-walled carbon nanotubes (f-MWCNTs) which dispersed in ethylene glycol. Tyurikova and Demidov [3] synthesized the magnetic nanofluids with Fe3O4 nanoparticles in a solvent, water-based using Oleic Acid and Mannitol

M. Hatami et al. / Journal of Molecular Liquids 250 (2018) 244–258

successfully preparation and verification of sustainability, while the industry can have a great future. Ferrofluids or magneto-hydrodynamic (MHD) nanofluids are a colloidal mixture of magnetic particles in a base fluid. MHD can be seen as significant role in exchangers, speakers, medical imaging, and drug delivery. In recent years, many studies on the thermal conductivity have been done with using different nanofluids. kV [4] studied the thermal conductivity and electrical conductivity of Bio-Glycol water mixed Al2O3 nanoparticles. Raei et al. [5] investigated the heat transfer performance and pressure drop specifications of Y-Al2O3/water nanofluid in a heat exchanger. Also, Hawwash et al. [6] studied the effect of using Al2O3 nanofluids as a working fluid for the solar water heater. One of the most application of nanofluids are cooling in microchannels where Azizi et al. [7] investigated the friction factor and convective heat transfer coefficients of copper nanofluids in a cylindrical microchannel heat sink. Sun et al. [8] analyzed the improved heat transfer and flow resistance achieved with drag reducing copper nanofluids. Sulochana and Sandeep [9] analyzed the heat transfer behavior and stagnation point flow of Cu–water nanofluid. Alten et al. [10] investigated the effect of Fe3O4 nanoparticles on thermal conductivity in heptane and in water with increasing volume concentration. Thakur et al. [11] used Fe3O4 nanofluid for recognition the magnetic field. Anghel et al. [12] investigated the in vitro studies with uses of Fe3O4/C12 nanoparticles. Kumar et al. [13] studied on effect of Fe3O4 nanofluid on heat transfer coefficient in the pipe of heat exchange and the results showed that the Nusselt number increase about 15.6%. Hosseinzadeh et al. [14] in an experimental work, investigated two parameters (heat transfer and friction factor) subjected to magnetic field on heat transfer. Also, Dibaei and kargarsharifabad [15] investigated the new achievements about heat transfer subjected to magnetic field using of Fe3O4 nanofluid, experimentally. Others synthesis experimental studies can be found in [16–18]. Researches on magnetic nanofluids is a new field and practical in industry especially for Fe3O4 nanoparticles, Bai et al. [19] synthesized a magnetic nanofluid, solvent-free with a core–corona–canopy structure based on polyaniline/Fe3O4 for the first time. Hosseinzadeh et al. [20] investigated the forced flow convective heat transfer of a magnetic nanofluid (Fe3O4 and water) while Rafiq et al. [21] studied the effect of Fe3O4 nanoparticles on impulse breakdown strength of mineral oil. The present work reviews the recent developments on Magnetohydrodynamic Fe3O4 nanofluid in different applications. Generally, nanofluids show outstanding properties for engineering application. Many Remarkable phenomena and valuable results have been provided and the topics such as thermal conductivity, viscosity, friction coefficient and other properties in this paper were investigated. 2. Recent studies 2.1. Magnetic field effect In this section recent studies and their main outcomes on the magnetic effect on Fe3O4 nanoparticles are presented. Sheikholeslami and Rashidi [22] studied the free convection heat transfer in an enclosure filled with Fe3O4–water nanofluid in presence of variable magnetic field. They considered the combined effects of MHD and FHD. In their study, CVFEM is used to solve the governing equations. The effects of Rayleigh number, Magnetic number, nanoparticle volume fraction and Hartmann number on the flow and heat transfer specifications have been analyzed. They found that increasing Rayleigh number, Magnetic number and nanoparticle volume fraction caused to augmentation of the Nusselt number but Nusselt number decreases with increase of Hartmann number. Esmaeili et al. [23] studied the effect of an external AC magnetic field on the convective heat transfer coefficients of magnetite nanofluids with different viscosities, basing on the hyperthermia principle. In their study, magnetite nanoparticles were synthesized by solvothermal method for more application as nanofluid in heat transfer analysis.

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Fig. 1. The effect of magnetic field frequency (Maximum field amplitude = 1500 A/m) on the h measurements of water- (right side) and EG-based (left side) magnetite nanofluids [23].

Briefly their obtained results showen in Fig. 1 says that the heat transfer characteristics of the examined magnetite nanofluids based on diverse concentrations of water and ethylene glycol were substantially increased under the influence of an alternating magnetic field. The ameliorate results were attributed to the heat generation resulted from the magnetic nanoparticles through Neel and/or Brownian Mechanisms. In an experimental study on the magnetic field effect, Sheikhbahai et al. [24] investigated the boiling heat transfer of Fe3O4/ethylene glycol-water nanofluids on a thin Ni-Cr wire with and without electric field at atmospheric pressure conditions. Results of their study are presented in Fig. 2 which indicated that addition of nanoparticles to the nanofluids resulted in notable increase in CHF. It is shown that the important reason for changes in boiling heat transfer parameters is heater surface modifications by nanoparticle deposition during nucleate boiling. Heating surface is coated by deposited nanoparticles during pool boiling of nanofluids. The deposited layer proliferate the surface wettability, resulting in noteworthy CHF enhancement. Brojabasi et al. [25] investigated the effect of hydrodynamic particle size on transmitted speckle pattern in water based ferrofluids containing functionalized Fe3O4 nanoparticles which size ranges from 15 to 46 nm induced light transmission and the magnetic field. As seen in Fig. 3, three water-based stable magnetic nanofluids containing Fe3O4 nanoparticles coated with (i) poly-acrylic acid (PAA) (ii) tetra-methyl ammonium hydroxide (TMAOH) and (iii) phosphate were used in their study. They reported that, in all three nanofluids, the transmitted light intensity showed two specified critical magnetic fields, corresponding to the onset of aggregation and the onset of zippering. Both the critical fields shift

Fig. 2. CHF for nanofluids with different volume fractions of nanoparticles [24].

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light intensity and its speckle profiles according to their evolution of scatters from dynamic to an approximately static state. The backscattered light intensity reduced with external magnetic field due to the reprieve in the light propagation inside magnetic nanofluid as a result of the formation of standing waves inside scatterers. It is observed that a small change in backscattered angle gives rise to a large diversity in backscattered light intensity against external magnetic field. 2.2. Friction and thermal studies

Fig. 3. Normalized transmitted light intensity as a function of external magnetic field from three different magnetic nanofluids in the same dispersion (water) [25].

towards lower magnetic fields, as the hydrodynamic particle diameters enhancement and as well showed a power law dependence on the hydrodynamic diameters. The effect of magnetic field is not studied just in experimental studies; it is also investigated in numerical and modeling studies. For instance, Sheikholeslami et al. [26] applied CVFEM for the force convection heat transfer in a lid driven semi annulus enclosure against of a non-uniform magnetic field. In summary of their results in Fig. 4 can be concluded that increasing volume fraction nanoparticle and Reynolds number cause Nusselt number to rise. But Nusselt number increase with decreases of Hartmann number. Furthermore, the heat transfer enhancement decreases with increase of Reynolds number while it decreases with increase of Hartmann number. Hatami et al. [27] used Fe3O4 nano-particles in a half-annulus cavity to study the effect of variable magnetic field (VMF) on their treatments. They found that in low Eckert numbers, increasing the Hartmann number make a decrease on the Nusselt number due to Lorentz force resulting from the presence of stronger magnetic field. In Fig. 5 a short outcome of Brojabasi and Philip [28] is presented. They analyzed the magnetic field induced changes in the backscattered

Some of the studies on this field not only focused on the heat transfer, but also they considered the effect of friction factor by adding these types of nanoparticles in the base fluid. Sundar et al. [29] investigated the friction factor and heat transfer of MWCNT–Fe3O4 nanofluid flow in a tube with longitudinal strip inserts, experimentally as shown in Fig. 6 The heat transfer and friction factor experiments were conducted for nanofluids in the volume concentrations from 0% to 0.3% and Reynolds number changed from 3000 to 22,000, and longitudinal strip inserts with variable aspect ratios as 1, 2, 4 and 12. From the results they concluded that the Nusselt number increment for 0.3% nanofluid flow in a tube without inserts is 32.72% and with inserts of aspect ratio 1 is 50.99% at a Reynolds number of 22,000. Also, friction factor enhancement for 0.3% nanofluid flow in a tube without inserts was 1.15-times and with inserts of aspect ratio 1 was 1.26-times for a Reynolds numbers of 22,000 compared to base fluid. Kumar et al. [30] performed for the experimental evaluation of friction factor, heat transfer and influence of various volume concentrations of Fe3O4 nanofluid flow in a double pipe heat exchanger with return bend in the presence of turbulent flow conditions. They analyzed two methods of heat transfer augmentation techniques were examined (a) active method and (b) passive method which their results indicated that the friction factor of nanofluid increases with increasing Reynolds numbers and particle concentrations while the heat transfer enhancement of Fe3O4 nanofluids increases with increase of Reynolds number and volume concentration (Figs. 7–8). Sundar et al. [31] performed an experimental study to estimate turbulent forced convective heat transfer and friction factor at different volume concentrations of Fe3O4 nanofluid. The applied nanofluid was a stable colloidal suspension of magnetite (Fe3O4) nanoparticles of middle diameter 36 nm. A sample result of this study is shown in Fig. 9 which reveal that in a plain tube with Reynolds number of 3000 and 22,000, the increment of heat transfer coefficient for 0.6% volume concentration of Fe3O4 nanofluid is 20.99% and 30.96%, respectively

Fig. 4. Effects of Hartmann number and Reynolds number on local Nusselt number Nu loc along hot wall when ϕ = 0.04 [26].


Fig. 5. Angular variation of backscattered light intensity from magnetic nanofluid in presence of external magnetic field with ramp rate 1 G/s [28].

compared to water. Also they showed that the enhancement of friction factor in a plain tube with 0.6% volume concentration of Fe3O4 nanofluid when compared to water is 1.09 times and 1.10 times for Reynolds number of 3000 and 22,000, respectively. In another study [32] they performed an experimental setup to estimate the turbulent forced convective heat transfer and friction factor at several volume concentrations of Fe3O4 nanofluid in a plain tube and with twisted tape inserts in the presence of turbulent flow conditions.

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Fig. 7. Number of transfer units (NTU) variation of water and nanofluids at different Reynolds numbers [30].

They estimated following equations of friction factor and heat transfer coefficient for water with various volume concentrations of Fe3O4 nanofluid in plain tube with and without inserts (Fig. 10). H 0:028 NuReg ¼ 0:223 Re0:8 Pr0:5 ð1 þ ϕÞ0:54 1 þ D 3000b Reb22000; 0bϕb0:6%; 3:19b Prb6:50; 0bH D b15

Fig. 6. Schematic representation of experimental setup used in [29].

ð1Þ

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Fig. 8. Experimental Nusselt number of water and nanocomposite nanofluid flow through a tube with longitudinal strip inserts [30].

Fig. 10. Experimental Nusselt number of water and Fe3O4 nanofluid in plain tube with and without twisted tape inserts [32].

H 0:017 f Reg ¼ 0:3790 Re−0:025 ð1 þ ϕÞ0:21 1 þ D

double pipe U-bend heat exchanger with and without wire coil inserts under rebellious flow conditions. As seen in Fig. 12, the heat transfer of nanofluids increases with increasing nanoparticles concentration and Reynolds number. There were more enhancements with decreasing pitch ratio of the wire coil inserts. The Nusselt number enhancement was about 14.7% for the nanofluid of 0.06% volume concentration compared to water data without inserts. Also, the Nusselt number was further increased to 32.03% for the same volume concentration (0.06%) of nanofluid flow in the heat exchanger with a wire coil insert of p/d = 1 at a Reynolds number of 28,954 compared with water.

ð2Þ

Results of Moraveji and Hejazian [33] are shown in Fig. 11 for a numerical investigation carried out to show the effect of flow rapidity and nanofluid concentration on average friction factor and Nusselt number by using CFD tools. The main objective of this study was examination of the effects of flow rate and nanofluid concentration on the friction factor and Nusselt number in a system without considering of magnetic field. The Nusselt number and correspondingly the amount of heat transfer enhanced with increasing the volume concentration and Reynolds number of nanoparticle. The friction factor enhanced by reduction the Reynolds number but raising the volume concentration has a low effect on friction factor and consequently it had an inconsiderable effect on the quantity of pressure drop in the tube. Finally, Sundar et al. [34] investigated the convective heat transfer, friction factor and other characteristics such as effectiveness and number of transfer units (NTU) of Fe3O4/water nanofluids flow in a

Fig. 9. Comparison of temperature distribution of different volume concentrations of nanofluid with water [31].

2.3. Viscosity and thermal effects To show the effect of viscosity of nanofluids containing Fe3O4 nanoparticles on the thermal applications, recent studies are presented here. Wang et al. [35] performed an experimental investigation on the viscosity of water based Fe3O4 nanofluid in presence of various customizable magnetic fields. They prepared the Fe3O4 by co-precipitation technique in various volume concentrations and making magnetic field induction by SV-10 viscometer. As they reported on Fig. 13, the viscosity of Fe3O4 nanofluid increases with increasing of solid volume concentration, magnetic induction and the decreasing of temperature. Sonawane and Juwar [36] tried to optimize the values of temperature, concentration and ultra-sonication time to minimize viscosity of

Fig. 11. Effect of nanofluid concentration and Reynolds number on the average Nu number [33].


Fig. 12. Experimental Nusselt number of 0.01% nanofluid flow in a double pipe Ubend heat exchanger with wire coil inserts [34].

nanofluid and maximize thermal conductivity. They indicated that viscosity of nanofluid increases with an increase in concentration of nanofluid, but decreases with an increase in ultra-sonication time and temperature of nanofluid. Also, thermal conductivity of nanofluid increased with increasing concentration of nanofluid, ultra-sonication time and temperature of nanofluid. Sundar et al. [37] investigates the viscosities and the efficient thermal conductivities of water-based nanofluids containing magnetic Fe3O4 nanoparticles, experimentally. They prepared the nanofluid by synthesizing Fe3O4 nanoparticles using the chemical precipitation technique, and then dispersed in distilled water using a sonicator. Also, they measured the thermal conductivity and viscosity of the nanofluid using the transient hot wire method and plate viscometer and an AR-100 rheometer cone, respectively. Their results revealed that viscosity enhancement was greater compared to thermal conductivity enhancement under the same temperature and volume concentration (Fig. 14). knf ¼ kbf ð1 þ 10:5ϕÞ0:1051

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Fig. 14. Experimental thermal conductivity of the nanofluid in comparison with the proposed Eq. (3) [37].

data. Their results showed that both viscosity and thermal conductivity increase by raising volume concentration. Moreover, temperature increment leads to increase in the thermal conductivity while decrease in the viscosity. The thermal the viscosity and conductivity indicate a nonlinear relationship with the nanoparticles concentration. Sundar et al. [39] synthesized a new kind of ND-Fe3O4 nanocomposite material by considering simple in-situ and wet-chemical reaction method. Their results (Fig. 15) show that the electrical conductivity of powder ND-Fe3O4 nanoparticles 26-times is higher than NDsoot. The thermal conductivity at temperature of 60 °C for 0.2% volume concentration of water, 20.80%, 40.60% and 60.40% EG/W nanofluid is 17.8%, 13.43%, 13.6% and 14.6%, respectively compared to its base fluids. The thermal conductivity enhancements of nanofluids depended on the particle concentrations and temperatures. Also, they concluded that viscosity and thermal conductivity of fluids prepared with ND-Fe3O4 nanocomposite are better than conventional single-phase nanoparticles.

ð3Þ 2.4. Thermal applications

where 0 b ϕ b 2.0%, 20 °C b T b 60 °C. To find a better model for viscosity and thermal conductivity of water-Fe3O4 nanofluid in terms of volume concentration and temperature, Bahiraei and Hangi [38] used neural network based on experimental

Most of the recent studies in thermal applications of magnetic Fe3O4 nanofluids are presented in this subsection. Sha et al. [40] investigated the effects of magnetic field strength and temperature on the convective

Fig. 13. Viscosity for various volume concentrations of Fe3O4 nanoparticles suspensions in water at 293 K under different magnetic inductions [35].

Fig. 15. Present data of thermal conductivity and viscosity for nanofluids at different volume concentrations and temperatures [39].

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Fig. 16. Comparison between experimental data of Fe3O4/water nanofluids with the correlation of Darcy's equation [40].

Fig. 18. Total entropy generation rate of rGO-Fe3O4 nanofluid as a function of velocity for several cases [42].

heat transfer of the Fe3O4/Water nanofluids. From their results (Fig. 16) it can be found heat transfer coefficients were dropped by applying a parallel constant and uniform magnetic field. The heat transfer coefficient of Fe3O4/water nanofluids was increased with the increasing temperature and decreased with the increasing magnetic field strength. The mechanism was examined by the following two main reasons; firstly: the influence of the Brownian motion on the convective heat transfer of Fe3O4/water nanofluids was very limited, the heat transfer increment couldn't be observed in the presence of low magnetic field strength and second: The decrease of the boundary layer thickness in connection with the reduced viscosity would lead to an reduction in the heat transfer increment at high temperature. In a numerical modeling of thermal application of nanofluids, Sheikholeslami [41] simulated the effect of Coulomb forces on nanofluid hydrothermal treatment by CVFEM. Reported results in Fig. 17 indicated that temperature gradient augments with enhance of Reynolds number and Coulomb forces. In another experimental study as shown, Mehrali et al. [42] investigated the entropy generation rate and heat transfer specifications of hybrid graphene-magnetite nanofluids under forced laminar flow that exposed to the permanent magnetic fields. For this aim, a nanoscale reduced graphene oxide-Fe3O4 hybrid was synthesized by using graphene

oxide, tannic acid and iron salts as the stabilizer and reductant. They observed that the heat transfer properties have been improved significantly in the presence of magnetic field. The conclusions of their analysis in Fig. 18 showed that the total entropy generation rate was reduced up compared to distilled water (up to 41%). Yu et al. [43] used the phase-transfer method for preparing stable kerosene-based Fe3O4 magnetic nanofluids and the effects of the measured temperatures, particle volume fraction, setting time on the thermal conductivity were investigated as shown in Fig. 19. The increment of the thermal conductivity is linearly with the volume fraction of Fe3O4 nanoparticles and the amount is up to 34.0% for 1.0 vol% nanofluid. Moraveji and Hejazian [44] studied the natural convection heat transfer in rectangular cavities with an inside oval-shaped heat source filled with Fe3O4/water nanofluid using finite element technique. The result indicated that adding nanoparticles did not led to an augmentation in the amount of Nusselt numbers, in the whole range of Rayleigh number, the different shapes of heat source, and volume fraction. Moreover, the heat source with ε = 0.99 led to higher Nusselt numbers than the case with ε = 0.9. Therefore, specifying and design the suitable geometry of the heat source can result in higher rates of heat transfer than using the nanofluid.

Fig. 17. Effects of Reynolds number and supplied voltage on average Nusselt number [41].

Fig. 19. Enhanced thermal conductivity as a function of the volume fraction for kerosene based Fe3O4 nanofluids [43].


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Fig. 20. Thermal conductivity of EG/W based nanofluid with influence of volume concentration [45].

As mentioned before, most of the studies in this field are experimental works which is more valuable. Sundar et al. [45] investigated the thermal conductivity of water and ethylene glycol mixture based using Fe3O4 nanoparticles, experimentally. The magnetic nanoparticles used in their analysis with a middle particle size of 13 nm were synthesized by chemical co-precipitation technique. A brief of their results are shown in Fig. 20 which reveals thermal conductivity of nanofluid increases with increase of temperature and particle volume concentration. Also, Abareshi et al. [46] in their experimental study measured the thermal conductivity of nanofluids prepared by dispersing the Fe3O4 nanoparticles in water as a base fluid in the presence of tetra-methyl ammonium hydroxide as a dispersant using the KD2 Pro Thermal Properties Analyzer which works based on the transient hot wire method. As depicted via Fig. 21, the thermal conductivity ratio of the nanofluids increases with increase in volume fraction and temperature as well as Sundar et al. [45] reported. Afrand et al. [47] studied the thermal conductivity of Fe3O4/water magnetic nanofluids experimentally and designed a precise and affective artificial neural network to predict the thermal conductivity ratio of the magnetic nanofluid (Fig. 22 shows its validation). Their experiments were carried out for different nanofluid samples under temperatures ranging from 20 °C to 55 °C with solid volume fractions of 0.1%, 0.2%, 0.4%, 1%, 2% and 3%. Eventually the experimental results showed that the maximum increment of thermal conductivity of nanofluid was about 90%, which happen at solid volume fraction of 3.0%.

The natural convective heat transfer of Fe3O4/Ethylene Glycol nanofluids around a tenuous platinum wire in the presence of electric field was observed in the experimental work of Asadzadeh et al. [48]. Results in Fig. 23 showed increasing Rayligh number and electric field intensity decreased and increased heat transfer enhancement, respectively. Lee et al. [49] expressed the effects of pressure on the CHF in a pool of water-based nanofluids of alumina and magnetite (Al2O3 and Fe3O4) nanoparticles using Ni–Cr wire as shown in Fig. 24. To estimate the effect of pressure on the CHF enhancement of water-based nanofluids, pool boiling CHF experiments using pure water were first done at 101 kPa (atmospheric pressure) to 1100 kPa. Fig. 25 which is extracted from their study says that using of water-based nanofluids of Fe3O4 and Al2O3 nanoparticles can considerable enhance the CHF in a pool at higher pressures and the bubble frequency of the nanofluids was about 2 times higher than that for pure water in the span of atmospheric pressure to 1100 kPa. To evaluate thermal effusively of Fe3O4 nanofluid, Raykar and Singh [50] designed and developed a Photo-acoustic (PA) sensor setup. The PA sensor is based on open cell mode (OPC) to measure acoustic signals from low concentration of nanoparticulate suspensions in ethylene glycol (EG). The obtained results showed that PA signal changes significantly with inclusion of Fe3O4 NPs in EG.

Fig. 21. The thermal conductivity ratio (k/kf) as a function of volume fraction at 30 K [46].

Fig. 23. Nu number versus Ra number for pure ethylene glycol [48].

Fig. 22. Comparison between experimental TCRs, correlation and ANN outputs [47].

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Fig. 26. Comparison of thermal conductivity data of Fe3O4 nanofluids with experimental and theoretical calculation results [51]. Fig. 24. Schematic of the pool boiling apparatus [49].

2.6. Synthesis works Thermal conductivities of magnetic Fe3O4 aqueous nanofluids prepared by co-precipitation method nanofluids were measured by Zhu et al. [51]. The nonlinear and abnormal thermal conductivities of nanofluids were mainly according to the nanoparticle alignment and clustering as presented in Fig. 26.

2.5. Thermo-physic studies Some of the recent studies which more focus on the thermo-physic field are presented here. Askari et al. [52] prepared Fe3O4 nanoparticles with a novel synthesis technique for decorated Graphene and its application as a kerosene-based nanofluid with the purpose of heat transfer increment. According to the results presented in Fig. 27, increase in Reynolds number and particles loading causes convective heat transfer coefficient to improvement. In addition viscosity of nanofluid increases by addition of particle loadings. Another study of viscosity and the thermal conductivity of Fe3O4 nanoparticles in paraffin is performed by Khedkar et al. [53] up to a volume fraction range of 0.01, 0.1 of nanoparticles. Transient hot-wire technique is used to measure the thermal conductivity of nanofluids. Nanofluids composition showing increment in both viscosity and thermal conductivity with volume fraction, furthermore percent increases in viscosity is very little as compared to thermal conductivity.

Fig. 25. Comparison of CHF data between pure water and 1 ppm of water-based nanofluids with magnetite (MWNF) and alumina (AWNF) nanoparticles [49].

In this section, it is tried to gather and discuss on the studies that focused on the Fe3O4 synthesis and analysis. Chicea and Goncea [54] measured the physical parameters for example conductivity, light scattering and surface tension coefficient. Their analysis showed a decrease in the surface tension coefficient with the enhancement of the nanoparticles concentration (Fig. 28), also they found a very fast increase of the conductivity with the increase of the nanoparticles volume fraction and this fast variation can be used to measure for low concentration, in the range 0–16,000 ppm. Syarif and Prajitno [55] synthesized the nanoparticles of Fe3O4 from local material of yarosite using precipitation technique, and rather stable water-Fe3O4 nanofluids were prepared. From results it can be found that CHF (Critical Heat Flux) of the same nanofluid was 155% larger than that of water and the thermal conductivity of the water-Fe3O4 nanofluid containing 20% citric acid was 3% larger than that of water (Table 1).

Fig. 27. Nusselt number with Reynolds number for base fluid and 0.1 wt% and 0.3 wt% of particle loading [52].


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Fig. 29. The increase of CHF of the Water-Fe3O4 nanofluids at various concentrations of Fe3O4 nanoparticles [56].

Fig. 28. The variation of the surface tension coefficient with the nanoparticle volume ratio, triangles and the linear fit, solid line [54].

Syarif and Prajitno [56] synthesized Fe3O4 nanoparticles for heat transfer by using precipitation technique via utilizing Fe2O3 nanoparticles extracted from local material of yarosite. The precipitation was performed by utilizing Fe3O4 powder that made by reducing the Fe2O3 using graphite (carbothermal process). The results indicated that the CHF of the nanofluids is larger than water, and increases by the increase of Fe3O4 nanoparticles concentration which is shown in Fig. 29. Stable magnetic nanofluids containing Fe3O4@Polypyrrole (PPy) nanoparticles were prepared via using a facile and novel method by Zhao and Nan [57]. Oxidant to polymerize pyrrole monomers and the FeCl3·6H2O was used as the iron source. Trisodium citrate was used as the reducing reagent. The particle size of the as-prepared Fe3O4@PPy can be easily controlled from 7 to 30 nm by adjusting the amount of pyrrole monomer. The steric stabilization and weight of the NPs affect the stability of the nanofluids. The as-prepared Fe3O4@PPy NPs showed super paramagnetic behavior with different saturation magnetizations (Fig. 30).

both the strength of heterogeneous reaction parameter and the strength of homogeneous reaction parameter and Surface drag force has direct relationship with the strength of magnetic field. In another study of Ferro-fluid application, Hayat et al. [60] used the magnetic nanofluid (Ferro fluid) between two parallel rotating disks with stretchable various rotating and stretching velocity influence of various pertinent parameters as presented in Table 3. The results showed that heat transfer rate reduce for increasing values of thermal slip parameter, and skin friction coefficient decrease by increasing velocity slip parameters. Afrand et al. [61] investigated the influence of nanoparticles concentration and temperature on the rheological behavior of Fe3O4-Ag/EG hybrid nanofluid, experimentally. They prepared stable and homogeneous

2.7. Other applications Du to wide range of application of Fe3O4-nanofluids, in this section more studies in this field in different applications are gathered and discussed. Sajid et al. [58] studied the heat exchange of a MHD magnetic nanofluid flow in a semi porous curved channel. So purpose of this research is to analyze the Joule heating impacts for the MHD flow of a Ferro-fluid in a semi porous curved channel. Results showed that the velocity profile decreases by increasing the value of Reynolds number, dimensionless radius of curvature (K), solid volume fraction and magnetic parameter (M). The absolute value of the skin friction coefficient increases for higher values of K, ϕ and Re, whereas it decreases by increasing the value of M (Fig. 31 and Table 2). Also, Hayat et al. [59] investigated the flow of Fe3O4 Ferro-fluid due to a rotating disk under homogeneous–heterogeneous reactions and computations for Nusselt number and skin friction coefficient are presented. As shown in Figs. 32 and 33, surface concentration reduced for

Fig. 30. Magnetization curve of the Fe3O4@PPy prepared under different amounts of pyrrole monomer at 160 °C: (A) 0 mL, (B) 0.1 mL, (C) 0.3 mL, (D) 0.5 mL [57].

Table 1 Thermal conductivity and CHF of the water-Fe3O4 nanofluid containing 0.1 g citric acid measured at 25 °C [55]. Sample

Viscosity Knf/KWater (mPa·s)

Nanofluid of (0.17 g Fe3O4/50 mL water)

0.73

NF = Nanofluids.

Increase (%)

CHFNF/CHFWater Increase (%)

0.255 3 1.03 0.2 1.002 (Maxwell) (Maxwell)

155 Fig. 31. Variation of the Reynold number Re for the two values of non-dimensional radius of curvature on temperature distribution θ(η) when M = 0.15, Pr = 10, Ec = 0.4 and ϕ = 0.4 [58].

254


Table 2 Numerical values of the Nusselt number − Re−1.2 Nus for various values K, M, φ, Re, Pr and s Ec [58]. K

M

ϕ

Re

Pr

Ec

−Re−1.2 s Nus

2 4 6 2

0.1

0.4

3

10

0.2

1.0959 1.3254 1.5433 1.9705 1.0959 0.2222 1.3179 1.2107 0.4611 1.5901 0.5955 0.0891 2.1260 1.8436 0.3436 1.9708 1.5334 0.2210

0.05 0.1 0.15 0.1

0.1 0.3 0.6 0.4

2 4 5 3

3 5 15 10

0.1 0.15 0.3

suspensions in various solid volume fractions and found that the viscosities of non-Newtonian samples decreased with the shear rates. Moreover consistency index substantially decreased with enhancing temperature and increased with an increase in the solid volume fraction as shown in Fig. 34. In another application of MWCNT and Fe3O4 nanofluids as shown in Fig. 35, Nabipour et al. [62] tested the absorption of CO2 using Sulfinol-M based nanofluids by an isothermal stirred high pressure vessel that has been prepared for their special research. They reported that by adding 0.02 wt% carboxyl fictionalized MWCNTs to Sulfinol-M, the equilibrium solubility increased to 23.2% compared to based-solvent. Also, an enhancement in the concentration of MWCNTs caused to a reduction in enhancement factor. Moreover, the measurements revealed that by increasing pressure the capacity of nanofluid enhanced to absorb more CO2 (Fig. 36). Nanofluids flow in simple tubes have a large application in all required industries, so the treatment of such nanofluids in these tubes has a large important. For instance, to estimate turbulent forced convective heat transfer and friction factor under turbulent flow conditions at different volume concentrations in tubes Mary and Sravani [63] study can guide us as their results are presented via Table 4. The Nusselt number and average heat transfer coefficient increased by increasing the particle concentration and flow, rapidity. Particle size is an important factor for example, the average temperature of nanofluid decreased by

Fig. 33. Influence of Schmidt number Sc on concentration profile ϕ(η) [59].

increasing that. Due to its fully developed conditions, heat transfer coefficient is constant throughout the circular channel. As and special application of L-shaped cavities, Jhumur and Bhattacharjee [64] numerically investigated the flow properties of unsteady MHD mixed convection inside L-shaped enclosure in the presence of magnetic nanofluid (Fe3O4-Water). Their mesh independency is shown in Fig. 37 and concluded that magnetic nanofluid causes significant effects on heat transfer rate. Furthermore, natural convection is more effective compared with mixed convection as higher values of Nu obtained for higher values of Gr numbers. To find the magnetic effect, they observed that enhancement of Hartmann (Ha) number, reduces both average temperature and Nusselt number, proportionally. In another CFD application, Kumar et al. [65] estimated the convective heat transfer and friction factor properties of Fe3O4 nanofluid flow in a two-pass double pipe U-bend heat exchanger in the Reynolds number range from 9000 to 24,000 at constant heat flux boundary conditions. The results showed that by increasing the Reynolds number and volume fraction, Nusselt number increased and friction factor decreased. Furthermore, the friction-factor is increased with increase of volume concentration. In addition, it was observed that the frictionfactor enhancement is low compared to the enhancement to the heat transfer for volume fraction intended in the results. In most application of numerical and experimental studies, authors try to optimize their outcome by optimization techniques such as artificial neural network (ANN), Genetic Algorithm (GA), Response Surface Methodology (RSM), etc. Aghayari et al. [66] evaluated and predicted the thermal conductivity of Fe3O4 nanofluid using experimental data at different volume fractions and temperatures. As seen, temperature and volume fraction were considered as network inputs and for output, thermal conductivity ratio is considered. Panitapu et al. [67] simulated natural convective heat transfer of Fe3O4-water nanofluid with different volume concentrations inside a

Table 3 Numerical values of Nusselt number at the lower and upper disks for different values of physical parameters [60].

Fig. 32. Local Nusselt number Nur (Re) − 1/2 at different values of Re [59].

γ3

γ1

ϕ

Re

M

K nf Kf

0.9 1.0 1.16 0.9

0.5

0.2

0.3

0.5

0.55853 0.52121 0.48857 0.55966 0.56062 0.70067 0.87827 0.55465 0.55089 0.55855 0.55857

0.6 0.7 0.5

0.3 0.4 0.2

0.4 0.5 0.3

0.6 0.7

θð0Þ

K nf Kf

θð1Þ

0.58602 0.54686 0.51261 0.58453 0.58330 0.72876 0.90705 0.59082 0.59551 0.58600 0.58598


255

Table 4 Water base fluid properties with different concentration of Fe3O4 nanoparticles [63].

Fig. 34. Power-law index versus temperature for non-Newtonian samples [61].

Volume-fraction (%)

Density (kg/m3)

Specific heat (J/kg-K)

Thermal conductivity (W/m-K)

Viscosity (kg/m-s)

0.02 0.1 0.3 0.6

996.53 999.88 1008.25 1020.806

4312.16 4844.82 6176.46 8173.92

0.609357 0.610788 0.614374 0.61978

0.0008038 0.0008292 0.0008949 0.0009064

square cavity in present of different temperatures on opposite walls. As shown in Fig. 38, the preliminary studies revealed that in 0.1% and 0.3% for the range of Rayleigh number the enhancement is b 10% for the volume fractions of data considered in the analysis, while a maximum increment of 29% is observed for a volume concentration of 0.6%. Dielectric specifications of a Natural ester based oil Fr3TM with the addition of surface modified Fe3O4 nanoparticles is considered by Peppas et al. [68]. Actually, the surface modification of the nanoparticles is an appropriate method to avoid nanoparticle agglomeration in insulating Nanofluids. From the AC breakdown voltage results shown in Tables 5, it is clear that the dielectric behavior of the Nanofluid is ameliorated compared to the natural ester oil. It appears that a 0.004% weight ratio improves the AC breakdown voltage pursuant to IEC 60156 about 7%. Due to excellent abilities of nanofluids in cooling processes, they are widely used in micro-channel heat sink cooling applications. Abubakar et al. [69] investigated the effect of temperature on the microchannel heat sink using Fe3O4-H2O4 magnetic nanofluid. Fig. 39 demonstrate that using this nanofluid with volume fraction of ϕ = 0.4 as working fluid, 0.04% decreases the temperature in comparison with pure water, and the temperature reduces to 0.07% at ϕ = 0.6 volume fraction, while using ϕ = 0.8 volume fraction there is more reduction in temperature to about 0.08%. Ellahi et al. [70] used an engine oil having Fe3O4 Magnetic nanoparticles as a base fluid to find the influence of aggregations in twodimensional heat transfer mixed convection flow of a nanofluid near a vertical stretching permeable sheet when the buoyancy force assists or opposes the flow. A part of their reported data is shown in Table 6 and it was obtained that the velocity of nanofluid decreased by increasing the particle volume friction and fractal dimensions. Furthermore, the velocity increases by increasing the chemical dimensions and the radius of the gyration. The temperature of the nanofluid is increased by

Fig. 35. The schematic of the experimental setup [62].

Fig. 36. Concentration of nanoparticles with sediment time [62].

Fig. 37. Variation of Nusselt (Nu) number with Grid Elements for Gr = 103 and τ = 5, at vertical heated wall [64].

256


Fig. 38. Graphs of Nu Vs ϕ for different volume concentrations [67].

Fig. 40. High shear viscosity as a function of temperature for different nanofluids at 100 Hz [71].

Table 5 Descriptive statistic for natural ester, mineral and nanofluid [68]. Descriptive statistic

Natural ester

Nanofluid

Mineral

Mean (kV) Std. deviation (kV) Skewness Kurtosis

65.4 12.0 −0.537 −0.049

69.7 12.9 0.221 −0.808

70.3 16.7 0.2295 −0.2474

alkyl chains of modifiers provide nanofluids better flow ability and less viscosity. 3. Conclusion Based on our experience in the nanofluid, two phase flows and optimizations which some of them are presented in [72–91], we decided to collect the recently studies in the magneto-hydrodynamic (MHD) nanofluids flow application using Fe3O4 nanoparticles. The studies include both numerical and experimental applications while some of them include optimization also. The papers were analyzed in seven different fields including the various applications such as in microchannels, Co2 storages, U-tubes, L shaped geometries in solar application channels, etc. Although the studies had valuable separate outcomes, but approximately all of them confirmed that by increasing the Reynolds number and volume fraction, Nusselt number increased and friction factor decreased. From this review study, it seems that more analysis in renewable applications is required due to lack of data in this field against its large importance of energy crisis.

Fig. 39. Average temperature distribution versus channel length for Re = 1400, ϕ = 0.6 [69].

increasing the volume friction, the chemical dimensions and the decrease of the gyration. Moreover, temperature decreases according to increment in the fractal dimensions. As the last application study in this field, Tan et al. [71] studied the connection between corona structure and specifications of solventfree Fe3O4 nanofluids. As seen in Fig. 40, three kinds of Fe3O4 solventfree nanofluids were prepared by using the modifier 3392, 6620 and 8415, respectively. In the Fe3O4 solvent-free nanofluids system, the Fe3O4 nanoparticles formed the core, and the shell was the ionic liquid. It reveals that solvent-free nanofluids have liquid-like behavior. Long

Table 6 Effects of the fractal dimension on the Skin-friction coefficient and the Nusselt number [70]. df

Nu Rex −1:2

Cf ReX −1:2

70 95 10

2.91731 2.39011 2.23785

−3.54086 −3.54109 −3.54113

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